Comparative performance analysis of metaheuristic algorithms for maximum power point tracking under partial shading conditions in PV systems

Abstract

Photovoltaic systems are one of the renewable energy systems that convert solar radiation directly into electricity. The relationship between current and voltage of PV system is nonlinear and it has only one point where power efficiency is greatest. Power efficiency mainly depends on atmospheric conditions such as irradiance and temperature. Therefore, various maximum power point tracking algorithms have been proposed in the literature to obtain maximum efficiency. The proposed traditional methods show high performance for maximum power point tracking under uniform irradiance and constant temperature. But another situation that affects the power efficiency is the partial shading condition and there are more maximum points on the output power curve in the partial shading conditions. For this reason, traditional methods are insufficient to reach global maximum power points. Metaheuristic algorithms have been proposed to solve this problem. In this paper, particle swarm optimization, gray wolf optimization and whale optimization algorithms were selected among the metaheuristic algorithms and comparative performance analysis were made in terms of convergence rate and efficiency under partial shading conditions. Obtained results were compared both graphically and numerically.

Keywords

• Photovoltaik systems
• Metaheuristic algorithms
• Particle swarm optimization
• Gray wolf optimization
• Whale optimization
• Partial shading conditions

FV sistemlerde kısmi gölgeleme koşullarında maksimum güç noktası takibi için metasezgisel algoritmaların karşılaştırmalı performans analizi

Öz

Fotovoltaik sistemler, güneş ışınımını doğrudan elektriğe dönüştüren yenilenebilir enerji sistemlerinden birisidir. FV sisteme ait akım ile gerilim arasındaki ilişki doğrusal değildir ve güç verimliliğinin en büyük olduğu tek bir nokta bulunmaktadır. Güç verimliliği esas olarak güneş ışınımı ve sıcaklık gibi atmosferik koşullara bağlıdır. Bu nedenle literatürde, maksimum verimliliği elde etmek için çeşitli maksimum güç noktası takibi algoritmaları önerilmiştir. Önerilen geleneksel yöntemler tek tip ışınım ve sabit sıcaklık koşulları altında maksimum güç noktası takibinde yüksek performans göstermektedir. Fakat güç verimliliğini etkileyen diğer bir durum, kısmi gölgeli koşuldur ve kısmi gölgeli koşullarda, çıkış gücü eğrisi üzerinde birden fazla maksimum nokta bulunmaktadır. Bu sebeple, geleneksel yöntemler global maksimum güç noktalarına ulaşmak için yetersiz kalmaktadırlar. Bu sorunu çözebilmek için metasezgisel algoritmalar önerilmiştir. Bu çalışmada, önerilen metasezgisel algoritmalar içerisinden parçacık sürü optimizasyonu, gri kurt optimizasyonu ve balina optimizasyonu algoritmaları seçilerek kısmi gölgeli koşullarda yakınsama hızı ve verimlilik açısından karşılaştırmalı performans analizleri yapılmıştır. Elde edilen sonuçlar hem grafiksel hem de sayısal olarak karşılaştırılmıştır.

Anahtar Kelimeler

• Fotovoltaik sistemler
• Metasezgisel algoritmalar
• Parçacık sürü optimizasyonu
• Gri kurt optimizasyonu
• Balina optimizasyonu
• Kısmi gölgeli koşullar

Kaynakça

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